Camera-based inspection systems are widely used to monitor operation of industrial processes. One example is in the food industry, where cameras are positioned at different locations along a production line that packages food, or that applies labels to food containers. Computer vision systems monitor the imagery collected by such systems to assure that the production process is proceeding as expected, without aberration or incident.
One of the functions performed by such industrial vision system is to sense and decode machine-readable markings to assure that correct components are being used. Again taking the food industry as an example, when assembling multi-part packaging, it is critical that lidded containers be topped with lids that correctly correspond to the container. For instance, if a container is correctly marked as containing chocolate-peanut ice cream, but is incorrectly capped with a lid indicating chocolate ice cream, serious consequences may result.
Similarly, many products include multiple labels. A bottle of catsup, for example, commonly includes a front label, a back label, and a neck label. Again, it is essential that such labels be applied in correct groupings.
Small barcode-like markings, termed Datamatrix codes, sometimes are included on packaging components and used to check that packaging components or labels are correctly used together. But these markings detract from the aesthetics of packaging. More recently, as detailed in Applicant's patent publication 20160267620, steganographic digital watermarks have been employed for such purpose.
As is familiar, a steganographic digital watermark comprises a subtle printed marking, e.g., included in packaging artwork, that conveys a plural-bit data payload in essentially invisible form. The presence of such marking is not generally apparent to an untrained consumer, who inspects a digitally watermarked package from a typical reading distance of 20 inches, in normal retail lighting (e.g., 75 to 100 foot-candles), and who has not previously been alerted to the watermark's existence. Yet, when a camera captures imagery of such a watermarked package, and the imagery is analyzed by corresponding watermark decoding software, the subtle markings can be discerned, and decoded to recover the plural-bit payload.
Due to the subtle nature of the markings, it is particularly important that imagery be captured using the best possible camera parameters for that environment (e.g., exposure interval, gain, aperture, etc.). Due to the inherent complexity of industrial production lines, and the myriad steps needed to prepare such lines for operation, it is desirable that the set-up of the companion inspection systems be as simple and quick as possible, so as to avoid compounding the complexity and set-up delays. Once the line is running, the inspection system must be reliable, so that the production line needn't be stopped to correct a problem with an imaging parameter or decoding operation.
In one aspect, the present technology involves varying camera capture parameters while the system repeatedly collects image data from one or more samples. An exemplary sample is a calibration target, printed with a grayscale gradient that ranges linearly from black to white. For each different set of camera capture parameters, the values of collected pixel data are compiled in a histogram, indicating a number of pixels counted with each respective level of gray (e.g., 0-255). An entropy metric is computed for each of the histograms. The set of capture parameters that yields the histogram with the highest entropy measurement is thereafter used to collect imagery from products, e.g., on a food packaging line, for watermark analysis. By so-doing, methods according to this aspect of the present technology guide selection of an optimal set of imaging parameters, to best allow machine detection of subtle features from imagery.
A camera used in such an inspection system might produce an image frame of 1280×960 pixels, yet a watermarked label or lid may occupy only a fraction of this area. Given the high speeds at which such inspection systems may operate, it is helpful for the decoder to know—in advance—in what parts of the captured image frame the watermark is likely to be found, so that the watermark decoder can concentrate its decoding efforts on such regions and extract the watermark payload before the next image is ready for processing.
Thus, a further aspect of the present technology involves analyzing reference imagery gathered by the inspection camera, to determine which parts of the image frame offer the highest probabilities of containing decodable watermark data.
The foregoing and other features and advantages of the technology will be more readily apparent from the following detailed description, which proceeds with reference to the accompanying drawings.